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Pipeline of the multiparameter identification workflow for sOCR and k M . For each sample, the optimal values of sOCR and k M are determined by iteratively simulating the O 2 transport and consumption dynamics of the system using the <t>PDE</t> toolbox in <t>MATLAB,</t> until the MSE (mean squared error) between predicted and measured O 2 concentration profiles is minimized.
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Pipeline of the multiparameter identification workflow for sOCR and k M . For each sample, the optimal values of sOCR and k M are determined by iteratively simulating the O 2 transport and consumption dynamics of the system using the <t>PDE</t> toolbox in <t>MATLAB,</t> until the MSE (mean squared error) between predicted and measured O 2 concentration profiles is minimized.
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MathWorks Inc matlab toolbox r2021b
Pipeline of the multiparameter identification workflow for sOCR and k M . For each sample, the optimal values of sOCR and k M are determined by iteratively simulating the O 2 transport and consumption dynamics of the system using the <t>PDE</t> toolbox in <t>MATLAB,</t> until the MSE (mean squared error) between predicted and measured O 2 concentration profiles is minimized.
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Pipeline of the multiparameter identification workflow for sOCR and k M . For each sample, the optimal values of sOCR and k M are determined by iteratively simulating the O 2 transport and consumption dynamics of the system using the PDE toolbox in MATLAB, until the MSE (mean squared error) between predicted and measured O 2 concentration profiles is minimized.

Journal: APL Bioengineering

Article Title: A sense of proximity: Cell packing modulates oxygen consumption

doi: 10.1063/5.0160422

Figure Lengend Snippet: Pipeline of the multiparameter identification workflow for sOCR and k M . For each sample, the optimal values of sOCR and k M are determined by iteratively simulating the O 2 transport and consumption dynamics of the system using the PDE toolbox in MATLAB, until the MSE (mean squared error) between predicted and measured O 2 concentration profiles is minimized.

Article Snippet: Basically, sOCR and k M were identified for each tested configuration by iteratively minimizing the mean squared error (MSE) computed between the measured O 2 concentration profile and the one obtained solving the non-dimensional form of Eqs. and using the partial differential equations (PDE) toolbox in MATLAB (R2021b).

Techniques: Concentration Assay